1.51 Robotics Autonomy Engineer - Locomotion
Tasks
- Apply domain randomization for sim to real transfer
- Automate evaluation across randomized scenarios
- Build scalable GPU accelerated training environments
- Collaborate with systems perception and embedded teams
- Design reinforcement learning locomotion pipelines
- Develop locomotion behaviors for quadruped and humanoid robots
- Develop reward functions and policy architectures
- Incorporate real world telemetry to improve model generalization
- Integrate physics simulation environments
- Lead deployment workflows from experiment to field validation
- Maintain simulation infrastructure for reproducibility
- Solve balance contact dynamics and high DOF coordination
- Validate locomotion on physical robots
Perks/Benefits
- N/A
Skills/Tech-stack
Adaptive methods | C++ | Contact dynamics | Continuous control | Control Theory | Domain Adaptation | Domain Randomization | GPU Computing | Isaac Lab | Isaac-Gym | Kinematics | Linux | Mujoco | Network inference | Neural Network | Neural network inference | Policy Networks | PyBullet | PyTorch | Python | ROS | ROS2 | Real Time | Real-time Systems | Reinforcement Learning | Reward Functions | Sim-to-Real | Sim-to-Real Transfer | Simulation infrastructure | System Identification | TensorFlow | Time Systems
Education
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